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Can AI Help to Detect and Cure Cancer?

By ­SC Viterbi News

November 6, 2017

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As director of the Center of Data, Algorithms, and Systems for Health at the University of Southern California's (USC) new Michelson Center for Convergent Bioscience, USC Viterbi professor Fei Sha will focus on applying the findings of statistical machine learning to medical science.

Among Sha's current projects is one to develop a machine-learning technology for analyzing tissue samples to diagnose breast cancer and produce more information, such as outcome and response to treatment.

Sha says the method entails feeding a computer sufficient biopsy data from the Cancer Genome Atlas to detect patterns, anomalies, and clinically relevant breast cancer subtypes, such as determining the response to estrogen-targeted therapies.

Another initiative Sha is engaged in is investigating how genetic biomarker variations of the immune system correlate to diversity in melanoma cancer cells, which could help spot the genetic cause of particularly hard-to-cure cancer subtypes and devise precise treatments for those cancers.

From USC Viterbi News
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